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Data-driven Subspace-based Islanding Detection Method for Grid-connected Photovoltaic Power Generation System
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Enlian CHEN1, Jianmin CHEN2, Yilian ZHANG1, Qinqin FAN3
Journal of Power Supply | 2026, 24(4) : 98 - 109
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Journal of Power Supply | 2026, 24(4): 98-109
• Renewable Energy Generation and Energy Storage •
Data-driven Subspace-based Islanding Detection Method for Grid-connected Photovoltaic Power Generation System
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Enlian CHEN1, Jianmin CHEN2, Yilian ZHANG1, Qinqin FAN3
Affiliations
  • 1.Key Laboratory of Transport Industry of Marine Technology and Control Engineering, Shanghai Maritime University, Shanghai 201306, China
  • 2.China Ship Development and Design Center, Wuhan 430060, China
  • 3.Logistics Research Center, Shanghai Maritime University, Shanghai 201306, China
Published: 2026-04-30 doi: 10.13234/j.issn.2095-2805.2026.4.98
Outline
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The grid-connected photovoltaic power generation technology has developed quickly in recent years, but it also poses risks such as the islanding effect. The realization of real-time monitoring of islanding effect is of significance for ensuring the stable operation of photovoltaic power generation systems. Therefore, aimed at the islanding fault of grid-connected photovoltaic power generation systems, a data-driven subspace-based islanding detection scheme is proposed. First, the fundamental wave from the voltage signal and the secondary harmonic signal of voltage at the point of common coupling are taken as the basis for islanding detection, and a voltage fundamental wave output predictor based on the subspace identification approach is designed. An adaptive filter for islanding detection is designed to track the fundamental wave from the voltage signal in real time, and the fundamental wave from the voltage signal is amplified to generate a residual signal. On this basis, an islanding fault detector is designed according to the residual signal and the secondary harmonic signal of voltage, so as to judge whether the system suffers the islanding fault. Finally, the effectiveness of the proposed approach was verified by simulation results.

Islanding detection  /  data-driven  /  subspace identification  /  grid-connected photovoltaic power generation system
陈恩怜, 陈建民, 张依恋, 范勤勤. 基于数据驱动子空间的光伏并网发电系统孤岛检测方法. 电源学报, 2026 , 24 (4) : 98 -109 . DOI: 10.13234/j.issn.2095-2805.2026.4.98
Enlian CHEN, Jianmin CHEN, Yilian ZHANG, Qinqin FAN. Data-driven Subspace-based Islanding Detection Method for Grid-connected Photovoltaic Power Generation System[J]. Journal of Power Supply, 2026 , 24 (4) : 98 -109 . DOI: 10.13234/j.issn.2095-2805.2026.4.98
Funding
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  • National Natural Science Foundation of China(62176150)
  • Shanghai University Capacity Building Project(20040501400)
  • Shanghai Pujiang Talent Program(22PJD030)
Appendix
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Year 2026 volume 24 Issue 4
23
2
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Article Info
doi: 10.13234/j.issn.2095-2805.2026.4.98
  • Receive Date：2023-10-13
  • Online Date：2026-10-29
  • Published：2026-04-30
Article Data
Affiliations
History
  • Received：2023-10-13
  • Revised：2024-03-03
  • Accepted：2024-03-09
Funding
National Natural Science Foundation of China(62176150)
Shanghai University Capacity Building Project(20040501400)
Shanghai Pujiang Talent Program(22PJD030)
Affiliations
    1.Key Laboratory of Transport Industry of Marine Technology and Control Engineering, Shanghai Maritime University, Shanghai 201306, China
    2.China Ship Development and Design Center, Wuhan 430060, China
    3.Logistics Research Center, Shanghai Maritime University, Shanghai 201306, China
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https://castjournals.cast.org.cn/joweb/dyxb/EN/10.13234/j.issn.2095-2805.2026.4.98
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